Becoming a Secure and Compliant Data-Driven Healthcare Organization

Data is everywhere in healthcare — from medical records, clinical trials, and genomics, to claims and billing data. This wealth of information offers tremendous opportunity for improving patient outcomes and reducing healthcare costs. Healthcare organizations are moving towards becoming secure and data-driven — which means leveraging data and insights to drive actionable intelligence and improving care delivery.

However, many healthcare organizations struggle with their data analytics and security infrastructures. While surrounding industries are bolstering their capabilities to be data-driven, the healthcare industry is beginning to face increased pressure to mitigate risk and demonstrate value. The healthcare industry is facing unprecedented challenges to protect patients and personal data, honor privacy requirements, and comply with the new Meaningful Use (MU) Stage 3 Stage Requirements, as well as other payer and provider regulatory requirements.

Please join Anurag Rai, Principal, Cyber Security Services, Healthcare Cybersecurity, KPMG LLP, Rajan Behal, Managing Director, Cyber Security Services, KPMG LLP, and Joseph Davis, Chief Security Advisor for Healthcare in the US Cybersecurity Solutions Group for Microsoft, for a discussion around the structural, organizational, and technical challenges facing healthcare organizations on their journey towards becoming secure and data-driven. We will discuss how organizations can modernize their analytics infrastructure, implement secure controls and risk governance, unify disparate data sources regardless of where they reside, reduce time to insight, and operationalize AI and machine learning.

Topics to be explored:

• Structural, organizational, and technical challenges that healthcare organizations face on their journey towards becoming secure and data-driven
• How organizations can modernize their analytics infrastructure, implement secure controls and risk governance.
• How to unify disparate data sources regardless of where they reside, reduce time to insight, and operationalize AI and machine learning.